Propofol in combination with remifentanil is useful for medical procedures that require moderate sedation and analgesia. Both drugs are rapid acting and quickly dissipate once administration is terminated. They interact synergistically with one another,1 requiring less of each drug to achieve a desired effect when used in combination. For example, a synergistic interaction is present for loss of response to laryngoscopy1–3 and moderately painful stimuli,4 and to a lesser extent for loss of responsiveness.1–3,5
Propofol and combinations of propofol with an opioid have been used to block the response to noxious stimuli during procedures in spontaneously breathing patients in the context of moderate sedation.6–11 In this setting, it is preferable to block the response to moderate noxious stimuli while avoiding intolerable ventilatory depression and minimizing loss of responsiveness.
The aim of this study was to explore the effects of selected combinations of remifentanil and propofol. Effects of interest included a loss of response to esophageal instrumentation (EI), a loss of responsiveness, and intolerable ventilatory depression. A secondary aim was to use these observations to create response surface models for each effect measure. We hypothesized that in a large percentage of volunteers, selected remifentanil-propofol effect-site concentrations (Ces) would allow EI but avoid intolerable ventilatory depression and that the drug interaction for these effects would be synergistic.
Volunteer Recruitment and Instrumentation
After approval by the IRB at the University of Utah, informed written consent was obtained from 12 male and 12 female (nonpregnant/nonlactating) volunteers. Eligible volunteers had an ASA physical status of I or II, were nonsmokers, 18 years of age or older, and had a body mass index between 18 and 28 kg · m−2. Volunteers were not eligible if they had a history of significant alcohol or drug abuse, allergy to opioids or propofol, sleep apnea, or chronic drug requirements or medical illnesses that are known to alter the pharmacokinetics or pharmacodynamics of opioids or IV anesthetics.
After overnight fasting, volunteers had a 20-gauge IV catheter placed for fluid and drug administration. A maintenance infusion of 0.9% sodium chloride was administered at 1 mL · kg−1 · h−1 throughout the study period. In addition, a 20-gauge arterial catheter was placed in a radial artery for continuous arterial blood pressure monitoring and intermittent arterial blood gas analyses. Volunteers were monitored with an electrocardiogram, pulse oximeter, noninvasive blood pressure, and expired carbon dioxide and inspired oxygen monitor. Inspired and expired airway flow and volumes were measured using a pneumotachometer (Novametrix, Louisville, KY) attached to a tight-fitting mask. All volunteers received oxygen by facemask at 2 L · min−1. A Mapleson E circuit was used to provide manual ventilation if required to maintain adequate oxygenation and ventilation. Before administration of the study drugs, volunteers were treated with 0.2 mg glycopyrrolate to prevent bradycardia and 30 mL sodium citrate by mouth.
The study was an open-label, randomized, parallel group study using a crisscross design as described by Short et al.12 to assess drug interactions. Each volunteer was randomly assigned to 1 of 2 groups: a basal infusion group of remifentanil, or propofol. Each group was further randomized to receive 3 of 6 possible sets of escalating predicted target Ces (Appendix 1). For each set, one drug was stepped through 5 predetermined Ce targets (primary drug) while the second drug was held at a constant Ce (secondary drug). After each set, the infusions were stopped until predicted Ces for both drugs returned to near 0, at which time the next set would begin. This design provided 61 possible pairs: one at baseline before drug administration, 30 for the remifentanil basal infusion group, and 30 for the propofol basal infusion group.
Based on prior work,1,5,13 8 to 9 volunteers were randomly assigned to 8 of the 12 sets (sets 1–4 of the remifentanil and propofol groups) of concentration pairs in the anticipated transition zone (<5.0 ng · mL−1 and 3.3 μg · mL−1 for remifentanil and propofol, respectively) and 1 to 2 volunteers to the remaining 4 sets (sets 5 and 6 of the remifentanil and propofol groups) anticipated to be near maximal effect. The predicted target Ces ranged from 0.0 to 6.4 ng · mL−1 for remifentanil and 0.0 to 4.3 μg · mL−1 for propofol. The study was designed so each experiment could be completed within 10 hours.
Drug Delivery and Effect Measures
Target-controlled infusions were administered using computer-controlled infusion pumps (Pump 22; Harvard Apparatus, Ltd., Holliston, MA) and drug infusion software (STANPUMPa). Pharmacokinetic parameters published by Minto et al.14 were used for remifentanil and Schnider et al.15 for propofol. Effect measurements began 5 minutes after predicted Ces reached the targeted concentrations.
At each target concentration pair, volunteers underwent an assessment period consisting of 3 measures. First, an assessment of responsiveness was made using the Observer's Assessment of Alertness/Sedation (OAA/S) scale (Table 1).16 A loss of response was defined as an OAA/S score = 1. Second, an assessment of respiratory rate was made using the capnography tracing. Intolerable ventilatory depression was defined as a respiratory rate of ≤4 breaths in a 1-minute time window. During pilot studies, we arrived at this respiratory rate cutoff based on several observations: at <4 breaths per minute, (1) there was a consistent decrease in the pulse oximeter saturation (SpO2) levels (a rapid decrease from 100 to low 90s) in volunteers, (2) the end-tidal CO2 began to increase above 50 mm Hg, and (3) without manual bag mask ventilation, the volunteers would become hypoxic. Third, an assessment of response to EI was made. A 42F (14 mm diameter, 215542; Teleflex Medical, Research Triangle Park, NC) blunt end bougie was placed through the oropharynx and advanced 40 cm into the esophagus. Loss of response to EI was defined as no gag reflex, no voluntary or involuntary movement, and no change in heart rate or arterial blood pressure >20% from baseline values recorded just before instrumentation. Each volunteer had 16 assessment periods (1 at baseline and 5 in each of 3 sets).
Volunteers were verbally prompted to breathe if there were <2 breaths in 30 seconds. If SpO2 was <95% on 2 L per minute of facemask oxygen or expired CO2 levels were >55 mm Hg and they did not respond to prompts to breathe, mask ventilation was provided. If airway obstruction was present, the airway was opened using a head tilt and chin lift and/or placement of an oral pharyngeal airway. If volunteers developed a mean arterial blood pressure or heart rate <20% of baseline, drug administration was terminated and the washout period begun. Ephedrine 5 to 10 mg was administered IV to treat hypotension as needed.
Response Surface Models
Using modeling software (MATLAB R2008b; MathWorks, Inc., Natick, MA), binary data (presence or absence of a response) for loss of response to EI and onset of intolerable ventilatory depression were fit to a Greco model17 adjusted for categorical data18 using Equation 1. For loss of responsiveness, a previously reported model based on data collected in volunteers in a similar manner was used.5
P(LR = 1 | CR, CP) is the probability of loss of response at a given remifentanil (CR) and propofol (CP) concentration. Emax is the maximal effect (i.e., loss of response to EI) and is 1 for categorical data. CR and CP are the predicted Ces of remifentanil and propofol (ng · mL−1 and μg · mL−1) as predicted by STANPUMP. C50R and C50P are the concentrations of remifentanil and propofol that alone achieve 50% probability of no response. The parameter γ determines the slope along the sigmoid surface, and α is the drug interaction term.
Models were built using a naïve pooled technique.19 Effect ranged from 0 (100% probability of response) to 1 (100% probability of no response). Model parameters were determined using an iterative approach minimizing the −2 log likelihood (−2LL), presented in Equation 2.
N is the number of observations made for all volunteers combined, Ri is the observed response, and P is the corresponding probability of loss of response.
To characterize variability, coefficients of variation (CVs) for each model parameter were estimated using a bootstrap technique. One thousand subsamples were randomly drawn (with replacement) from the raw data, with each subsample containing the same number of data points as the raw data set. Estimates of model parameters were generated from each subsample using the same techniques described previously. The mean (μ) and standard deviation (σ) of the 1000 estimates were used to compute the CV for each model parameter (Equation 3).
The CV was computed in this manner at least 10 times for each effect measure. It was continued until the percentage change between the average of all iterations and the average from all previous iterations was <5%. The final averaged CV was reported.
For each effect measure, model fits were evaluated using a χ2 goodness-of-fit test. Response/no response data were divided into probability bins with at least 5 no response data points in each bin. The expected frequency of no response for each bin (Pi) was calculated by multiplying the mean predicted probability by the total number of observations in the bin. Observed frequency of no response (Oi) was the number of observations where no response occurred. The χ2 test statistic was computed using Equation 4:
k is the number of bins. The null hypothesis was that the expected (based on the model's prediction of probability of no response) and observed frequencies were from the same distribution and was rejected if the χ2 test statistic exceeded the χ2 critical value at a significance level of 5% with k-5 df (4 parameters used to compute expected frequency are estimated from the data).
Two graphical approaches were used to assess model fits. The first plot presented the observed responses and a topographical rendering of model predictions. A graphical representation of the model was created by plotting the 5%, 50%, and 95% iso-effect lines (isoboles) representing predicted remifentanil-propofol Ces that produce an equivalent effect. This format was used to illustrate the number of volunteers that developed a loss of response alongside model predictions of the same effect measure. The second plot presented the observed responses and a 3-dimensional rendering (response surface) of model predictions. This format was used to illustrate the differences between model predictions (ranging from 0 to 1 using Equation 1) and observed responses (either 0 or 1). An assessment of how well the model predictions fit the observations was made by calculating the percentage of predictions that agreed with observations. Agreement was defined as an absolute difference <0.5.
Comparison of Model Profiles
Topographical plots of models of loss of response to EI, loss of responsiveness, and intolerable ventilatory depression were superimposed on one another. Each plot included the 5%, 50%, and 95% isoboles. Visual inspection of superimposed isoboles was used to identify potential concentration pairs with a high probability of loss of response to EI, yet avoid loss of responsiveness or intolerable ventilatory depression.
All 24 volunteers (12 men and 12 women) completed the study. The mean ± SD of the height, weight, body mass index, and age were 174 ± 8 cm, 71 ± 12 kg, 23 ± 3 kg · m−2, and 25 ± 4 years, respectively.
Appendix 1 presents the observed responses for each effect measure over the 61 concentration pairs investigated. Seventeen assessment periods were completely or partially aborted at higher target concentrations because blood pressure and/or heart rate were <20% of baseline. Portions of 3 assessment periods were aborted because of inadequate oxygenation after maneuvers to correct it failed. Of the possible 384 evaluations and 61 possible concentration pairs, 367 were made for EI at 56 concentration pairs, 373 were made for loss of responsiveness at 58 concentration pairs, and 376 were made for intolerable ventilatory depression at 59 concentration pairs (Appendix 1).
For EI, some or all of the volunteers in 38 of the 56 target concentration pairs exhibited no response (105 of the 367 evaluations). Ten of the 38 concentration pairs consistently blocked the response to EI (Fig. 1). Responses at the remaining 28 concentration pairs were mixed (i.e., some volunteers responded, others did not). For example, with propofol at 2.7 μg · mL−1 and remifentanil at 0.8 ng · mL−1, 4 volunteers tolerated EI and 4 did not.
Of the concentration pairs that blocked the response to EI, 30 assessments at 19 concentration pairs had no intolerable ventilatory depression (Fig. 1A). Of those, 4 assessments at 4 concentration pairs between 0.0 and 0.8 ng · mL−1 for remifentanil and 3.3 and 4.3 μg · mL−1 for propofol consistently had no intolerable ventilatory depression and tolerated EI. All other pairs had a mixed response; some volunteers tolerated EI but had intolerable ventilatory depression whereas others did not. For example, with remifentanil at 1.6 ng · mL−1 and propofol at 2.0 μg · mL−1, 5 of 7 volunteers tolerated EI and 2 of those 5 had no intolerable ventilatory depression.
Of the concentration pairs that blocked the response to EI, 30 assessments at 19 concentrations pairs (not identical to the 30 above) had no loss of responsiveness (Fig. 1B). At 8 of the concentration pairs, 9 volunteers also had no intolerable ventilatory depression and no loss of responsiveness (Fig. 1C). For example, with propofol at 1.5 μg · mL−1 and remifentanil at 0.8 ng · mL−1, 2 of 8 volunteers tolerated EI with no intolerable ventilatory depression and no loss of responsiveness, but the other 6 did not tolerate EI.
Response Surface Models
With visual inspection of the raw data, it is clear that the development of intolerable ventilatory depression at high propofol, low remifentanil concentrations was beyond the range of target concentrations used in our study design. For model building purposes, 31 data points at higher concentrations taken from previous work in our laboratory as part of a study in similar volunteers conducted by Kern et al.1 were therefore included in our analysis. These additional data, presented in Appendix 2, were collected using the same drugs, drug delivery technique, and approach to assessment of respiratory rate. Four hundred seven data points were used to construct the model of intolerable ventilatory depression.
Model parameters, CV, and goodness-of-fit analysis for loss of response to EI and intolerable ventilatory depression are presented in Table 2. P values from the χ2 goodness-of-fit test confirmed the null hypothesis that predicted and observed frequencies were from the same distribution, indicating a good fit for each model. CVs ranged from 5% to 58%. More variability (i.e., larger CVs) was estimated about the α (interaction) model parameter. The positive alphas were consistent with a synergistic interaction for all models. The response surface models predicted transitions from responsive to unresponsive over a large range of the tested remifentanil and propofol concentrations (as indicated by the small γ parameter values).
Observed responses superimposed over response surface models for each effect measure are presented in Figure 2, A and C. In both models, predictions are consistent with observations; all volunteers above the 95% isobole are unresponsive, a large majority are unresponsive between the 50% and 95% isoboles, the responses are mixed between the 5% and 50% isoboles, and very few are unresponsive below the 5% isobole.
Isoboles in both models bow toward the origin indicating a synergistic interaction. The shape of the model of intolerable ventilatory depression and that of the model of EI were different. Isoboles for intolerable ventilatory depression (Fig. 2C) bow asymmetrically toward remifentanil illustrating the large influence of opioids on this effect measure. By contrast, isoboles for EI (Fig. 2A) bow symmetrically between remifentanil and propofol.
Agreement between model predictions and observations is presented graphically in Figure 2, B and D. For both models, agreement was high at concentration pairs below and above the slope of the response surface, but in the transition from 5% to 95%, the difference between predictions and observations was >0.5 at several of the observations. Using an absolute difference ≤0.5 as a cutoff for model goodness of fit, the percentage of model predictions consistent with observed responses was 79% and 81% for the EI (Fig. 2B) and intolerable ventilatory depression (Fig. 2D) models, respectively.
Superimposed topographical plots of the loss of responsiveness, loss of response to EI, and intolerable ventilatory depression models are presented in Figure 3. A comparison of isoboles between models revealed no regions of remifentanil-propofol concentration pairs that would have a high probability (>95%) of no response to EI and a low probability (<5%) of intolerable ventilatory depression and loss of responsiveness. Disregarding loss of responsiveness, there is a region of low remifentanil (0–1.5 ng · mL−1) and high propofol (4–6 μg · mL−1) concentrations where there is a high probability (>80%–95%) of loss of response to EI and a moderate probability (40%–70%) of intolerable ventilatory depression.
We explored the effects of various combinations of remifentanil-propofol target concentrations on responsiveness, EI, and ventilatory depression. We hypothesized that in a large percentage of volunteers, selected concentration pairs would allow EI but avoid intolerable ventilatory depression. Our results in part confirmed this hypothesis; we found that low remifentanil (0.8 ng · mL−1) and high propofol (2–3 μg · mL−1) concentration pairs blocked the response to EI and avoided intolerable ventilatory depression in a majority of volunteers (Fig. 1). At higher propofol concentrations, the response to EI was blocked completely with no intolerable ventilatory depression, but the number of assessments was small, making it difficult to conclude that these concentration pairs would consistently lead to the desired response.
By comparison to studies by Kazama et al.20 and Drover et al.21 who also explored propofol requirements for EI, our results are somewhat different; we had to use higher concentrations to achieve conditions that would allow EI than what these authors have reported. The differences are likely attributable to variations in study design. Kazama et al. studied the use of target-controlled infusions in patients of various ages undergoing endoscopy. They reported a propofol C50 of 2.8 μg · mL−1 to blunt the response to EI in 17- to 49-year-old patients. Higher concentrations were required to blunt the gag reflex (C50 = 3.0 μg · mL−1). These are both lower than what we reported (C50 of 3.8 μg · mL−1). By design, they considered some movement and coughing not to be a response during endoscope placement. By comparison, our criteria to consider movement and heart rate change as responses are perhaps overly stringent and not reflective of clinical practice. Endoscopists may tolerate some level of patient movement or heart rate change to blunt rather than completely block the response to EI.
Drover et al.21 have studied the use of target-controlled infusion in pediatric patients aged 3 to 10 years old undergoing endoscopy. Similar to Kazama et al., minimal movement was not considered a response to EI. They reported a propofol C50 of 3.7 μg · mL−1. Drover et al. also explored how a remifentanil infusion would alter propofol requirements for EI. Using a continuous remifentanil infusion of 0.025 μg · kg−1 · min−1, the propofol requirement decreased to 2.8 μg · mL−1. For ease of comparison, we simulated this remifentanil infusion in a 55-year-old man (75 kg, 175 cm), which led to a steady-state predicted remifentanil Ce near 0.7 ng · mL−1. This concentration pair is consistent with our findings and very close to the 50% isobole we reported in Figure 2. Drover et al. also explored 0.05 and 0.10 μg · kg−1 · min−1 remifentanil infusion rates, which, when simulated in the same demographic, led to remifentanil Ces of 1.4 and 2.8 ng · mL−1, but patients developed significant respiratory depression requiring positive pressure ventilation. They concluded that lower remifentanil infusion rates may be more appropriate for pediatric endoscopies.
In addition to defining the loss of response to EI, we also sought to characterize the extent of intolerable ventilatory depression and loss of responsiveness over the same set of target remifentanil and propofol concentrations. We found that many of the volunteers tolerated EI and did not develop intolerable ventilatory depression, but this profile of responses was highly variable. At the same concentration pair, some volunteers would tolerate EI, others would not; some would have significant ventilatory depression, others would not. The raw data revealed no pattern between volunteers who tolerated EI and those who had intolerable ventilatory depression. A majority of the volunteers who tolerated EI without significant ventilatory depression were at target concentration pairs consisting of high propofol, low remifentanil levels (Fig. 1A). Similarly, we found that many of the volunteers tolerated EI and did not lose responsiveness, but this profile was also quite variable (Fig. 1B). By contrast, a majority of the volunteers that tolerated EI and did not lose responsiveness were at target concentration pairs consisting of high remifentanil, low propofol levels. Finally, there were very few volunteers who tolerated EI with no intolerable ventilatory depression and no loss of responsiveness.
With regard to intolerable ventilatory depression, we made our evaluations in an unstimulated state. This was done to facilitate data collection using the capnograph, mimicking the scenario whereby patients receive anesthetics to blunt the response to a brief, painful stimulus followed by a period of relatively little stimulus, and to explore the impact this dosing approach has on ventilatory function. It is conceivable that observations of respiratory rate during stimuli such as calling their name during the OAA/S assessment would increase their ventilatory rate and shift the observed onset of intolerable ventilatory depression to higher concentrations.
We also chose respiratory rate as a measure of ventilatory function because of its familiarity among practitioners and its availability on many physiologic monitors. There are limitations to this measure. For example, we did not account for tidal volume; we acknowledge that minute volume may have been adequate to achieve both oxygenation and ventilation despite a slow respiratory rate. Many volunteers achieved tidal volumes >1000 mL at slow respiratory rates. Furthermore, we did not account for changes in arterial CO2 on respiratory drive as many other authors have.22–25 Nevertheless, in the setting of moderate sedation, most clinicians would agree that a ventilatory rate of ≤4 per minute is concerning.
Response Surface Models
We constructed a response surface model for loss of response to EI and the presence of intolerable ventilatory depression. Both graphical and statistical approaches indicated that the models fit the observed data well. From a graphical perspective (Fig. 2), the models appear to capture the transition from responsive to unresponsive well and this was confirmed by the χ2 analysis and percentage of model predictions consistent with observed responses. We hypothesized that the interaction between these drugs would be synergistic for both effect measures. Our results confirmed this hypothesis as illustrated by the positive α values presented in Table 2.
To our knowledge, there is no prior interaction model for EI. Judged in terms of the concentrations required to blunt the response, the stimulus associated with EI is much less than what we previously reported for loss of response to laryngoscopy but similar to reports by Bouillon et al.2 (Table 2). For laryngoscopy, we reported remifentanil and propofol C50 values for loss of response to laryngoscopy of 48.9 ng · mL−1 and 5.6 μg · mL−1, respectively,1 and Bouillon et al. reported 9.0 ng · mL−1 and 5.6 μg · mL−1, respectively. With regard to intolerable ventilatory depression, prior work by Nieuwenhuijs et al.23 explored the onset of respiratory depression at remifentanil-propofol concentrations ranging from 0.0 to 2.0 ng · mL−1 and 0.0 to 2.0 μg · mL−1, respectively. They used a 50% decrease from baseline minute ventilation as their effect measure (i.e., presence or absence of respiratory depression). They constructed a response surface model from their data using a nonlinear pharmacodynamic model structure. Although the effect measures and model constructs were different than ours, the C50 values reported were similar considering the range of drugs they tested (4.2 vs 3.3 ng · mL−1 for remifentanil and 6.8 vs 15.8 μg · mL−1 for propofol).
To further explore the behavior of propofol in combination with remifentanil, we compared model predictions from 3 response surfaces: the 2 presented in this study and a previously reported response surface for loss of responsiveness.5 In attempting to orient oneself to the clinical meaning of response surfaces, a simple “take home” message is that target concentrations of approximately 2 ng · mL−1 remifentanil and 2 μg · mL−1 propofol produce approximately a 50% probability of no response to EI, no response to verbal and tactile stimuli, and intolerable ventilatory depression. Similarly, target Ces of 1 ng · mL−1 remifentanil and 1 μg · mL−1 propofol have a low probability (i.e., 5%) and concentrations >3 ng · mL−1 for remifentanil and 3 μg · mL−1 have a high probability (i.e., 95%) (Fig. 3) of producing those end points.
As illustrated in Figure 3, model predictions from each model had considerable overlap. This was consistent with our observations; there was no set of concentration pairs that consistently provided conditions for EI but avoided intolerable ventilatory depression and loss of responsiveness.
In all models, the zone of transition from responsiveness to unresponsiveness (between the 5% and 95% isoboles) covered a wide range of remifentanil and propofol Ces. In fact, some of the C50 values are outside the range of predicted concentrations we used during data collection. This is a limitation of our study design. We designed our study with the intent of making assessments over a range of concentrations that were below, at, and above the concentrations necessary to produce a loss of response to EI or intolerable ventilatory depression. In a majority of our observations, volunteers were either responsive or within the transition zone from responsive to unresponsive. Few of our observations were made where responses were completely blocked. With relatively little data at higher concentrations, our best fit models may have generated parameter sets that were skewed to higher concentrations because of the larger amount of response data at lower concentrations.
With the Greco model structure, when data are well distributed about the C50, the fit is reasonable. When the C50 is outside the range of concentrations evaluated, it is extrapolated; in this scenario, small changes in the data can result in large changes in the C50, particularly when the interaction is synergistic. Model predictions will fit the data well at concentrations where observations were made, but can inflate to clinically unrealistic levels for just one drug (i.e., propofol in the intolerable ventilatory depression model). When this occurs, the α (interaction) term must also increase to ensure that the model characterizes the data-rich portions of the response surface. Caution should be used when interpreting the magnitude of the α parameter when C50 estimates lie well outside the range of drugs tested.
In summary, we explored the feasibility of blocking the response to EI in volunteers at various target Ce pairs of remifentanil and propofol. In general, our results suggest that although it is possible to identify target concentration pairs that produce significant sedation and analgesia while preserving responsiveness and adequate ventilation, rendering a patient completely unresponsive to EI requires target concentration pairs that produce a clinical state beyond moderate sedation. In comparison to other similar work and typical clinical practice, the criteria we used to define a loss of response to EI were perhaps too strict. Our results suggest that to stay within the boundaries of moderate sedation, it may be necessary to accept some discomfort and blunt rather than block the response to EI to always avoid intolerable ventilatory depression. Alternatively, it may also be necessary to accept brief unresponsiveness while instrumenting the esophagus. An important clinical feature in this setting is the ability to prompt patients to breathe. Clinicians may tolerate a loss of responsiveness as long as patients continue to breathe; however, in the presence of intolerable ventilatory depression, clinicians are likely to find a prolonged loss of responsiveness and the inability to prompt a patient to breathe unacceptable. In conclusion, our results represent a preliminary finding in healthy volunteers. Further work is warranted to validate these models in patients undergoing moderate to deep sedation for procedures that require EI.
Available from Steven L. Shafer, MD, at http://www.opentci.org/doku.php?id=code:code. Posted November 25, 2008. Last accessed June 3, 2010.
1. Kern SE, Xie G, White JL, Egan TD. A response surface analysis of propofol-remifentanil pharmacodynamic interaction in volunteers. Anesthesiology 2004;100:1373–81
2. Bouillon TW, Bruhn J, Radulescu L, Andresen C, Shafer TJ, Cohane C, Shafer SL. Pharmacodynamic interaction between propofol and remifentanil regarding hypnosis, tolerance of laryngoscopy, bispectral index, and electroencephalographic approximate entropy. Anesthesiology 2004;100:1353–72
3. Mertens MJ, Olofsen E, Engbers FH, Burm AG, Bovill JG, Vuyk J. Propofol reduces perioperative remifentanil requirements in a synergistic manner: response surface modeling of perioperative remifentanil-propofol interactions. Anesthesiology 2003;99:347–59
4. Johnson KB, Syroid ND, Gupta DK, Manyam SC, Pace NL, LaPierre CD, Egan TD, White JL, Tyler D, Westenskow DR. An evaluation of remifentanil-sevoflurane response surface models in patients emerging from anesthesia: model improvement using effect-site sevoflurane concentrations. Anesth Analg 2010;111:387–94
5. Johnson KB, Syroid ND, Gupta DK, Manyam SC, Egan TD, Huntington J, White JL, Tyler D, Westenskow DR. An evaluation of remifentanil propofol response surfaces for loss of responsiveness, loss of response to surrogates of painful stimuli and laryngoscopy in patients undergoing elective surgery. Anesth Analg 2008;106:471–9
6. Tosun Z, Aksu R, Guler G, Esmaoglu A, Akin A, Aslan D, Boyaci A. Propofol-ketamine vs propofol-fentanyl for sedation during pediatric upper gastrointestinal endoscopy. Paediatr Anaesth 2007;17:983–8
7. Tosun Z, Esmaoglu A, Coruh A. Propofol-ketamine vs propofol-fentanyl combinations for deep sedation and analgesia in pediatric patients undergoing burn dressing changes. Paediatr Anaesth 2008;18:43–7
8. Fatima H, DeWitt J, LeBlanc J, Sherman S, McGreevy K, Imperiale TF. Nurse-administered propofol sedation for upper endoscopic ultrasonography. Am J Gastroenterol 2008;103:1649–56
9. VanNatta ME, Rex DK. Propofol alone titrated to deep sedation versus propofol in combination with opioids and/or benzodiazepines and titrated to moderate sedation for colonoscopy. Am J Gastroenterol 2006;101:2209–17
10. Cohen LB, Delegge MH, Aisenberg J, Brill JV, Inadomi JM, Kochman ML, Piorkowski JD Jr. AGA Institute review of endoscopic sedation. Gastroenterology 2007;133:675–701
11. Lichtenstein DR, Jagannath S, Baron TH, Anderson MA, Banerjee S, Dominitz JA, Fanelli RD, Gan SI, Harrison ME, Ikenberry SO, Shen B, Stewart L, Khan K, Vargo JJ. Sedation and anesthesia in GI endoscopy. Gastrointest Endosc 2008;68:815–26
12. Short TG, Ho TY, Minto CF, Schnider TW, Shafer SL. Efficient trial design for eliciting a pharmacokinetic-pharmacodynamic model-based response surface describing the interaction between two intravenous anesthetic drugs. Anesthesiology 2002; 96:400–8
13. Dahan A, Nieuwenhuijs DJ, Olofsen E. Influence of propofol on the control of breathing. Adv Exp Med Biol 2003;523:81–92
14. Minto CF, Schnider TW, Egan TD, Youngs E, Lemmens HJ, Gambus PL, Billard V, Hoke JF, Moore KH, Hermann DJ, Muir KT, Mandema JW, Shafer SL. Influence of age and gender on the pharmacokinetics and pharmacodynamics of remifentanil. I. Model development. Anesthesiology 1997;86:10–23
15. Schnider TW, Minto CF, Shafer SL, Gambus PL, Andresen C, Goodale DB, Youngs EJ. The influence of age on propofol pharmacodynamics. Anesthesiology 1999;90:1502–16
16. Chernik DA, Gillings D, Laine H, Hendler J, Silver JM, Davidson AB, Schwam EM, Siegel JL. Validity and reliability of the Observer's Assessment of Alertness/Sedation Scale: study with intravenous midazolam. J Clin Psychopharmacol 1990;10: 244–51
17. Greco WR, Bravo G, Parsons JC. The search for synergy: a critical review from a response surface perspective. Pharmacol Rev 1995;47:331–85
18. Bol CJ, Vogelaar JP, Tang JP, Mandema JW. Quantification of pharmacodynamic interactions between dexmedetomidine and midazolam in the rat. J Pharmacol Exp Ther 2000;294:347–55
19. Somma J, Donner A, Zomorodi K, Sladen R, Ramsay J, Geller E, Shafer SL. Population pharmacodynamics of midazolam administered by target controlled infusion in SICU patients after CABG surgery. Anesthesiology 1998;89:1430–43
20. Kazama T, Takeuchi K, Ikeda K, Ikeda T, Kikura M, Iida T, Suzuki S, Hanai H, Sato S. Optimal propofol plasma concentration during upper gastrointestinal endoscopy in young, middle-aged, and elderly patients. Anesthesiology 2000;93:662–9
21. Drover DR, Litalien C, Wellis V, Shafer SL, Hammer GB. Determination of the pharmacodynamic interaction of propofol and remifentanil during esophagogastroduodenoscopy in children. Anesthesiology 2004;100:1382–6
22. Bouillon T, Bruhn J, Radu-Radulescu L, Andresen C, Cohane C, Shafer SL. Mixed-effects modeling of the intrinsic ventilatory depressant potency of propofol in the non-steady state. Anesthesiology 2004;100:240–50
23. Nieuwenhuijs DJ, Olofsen E, Romberg RR, Sarton E, Ward D, Engbers F, Vuyk J, Mooren R, Teppema LJ, Dahan A. Response surface modeling of remifentanil-propofol interaction on cardiorespiratory control and bispectral index. Anesthesiology 2003;98:312–22
24. Romberg R, Olofsen E, Sarton E, Teppema L, Dahan A. Pharmacodynamic effect of morphine-6-glucuronide versus morphine on hypoxic and hypercapnic breathing in healthy volunteers. Anesthesiology 2003;99:788–98
25. Romberg R, Sarton E, Teppema L, Matthes HW, Kieffer BL, Dahan A. Comparison of morphine-6-glucuronide and morphine on respiratory depressant and antinociceptive responses in wild type and mu-opioid receptor deficient mice. Br J Anaesth 2003;91:862–70
Name: Cris D. LaPierre, BS.
Contribution: This author helped conduct the study, analyze the data, and write the manuscript.
Attestation: Cris D. LaPierre has seen the original study data, reviewed the analysis of the data, and approved the final manuscript.
Conflicts of Interest: Cris D. LaPierre reported no conflicts of interest.
Name: Ken B. Johnson, MD.
Contribution: This author helped design the study, conduct the study, analyze the data, and write the manuscript.
Attestation: Ken B. Johnson has seen the original study data, reviewed the analysis of the data, approved the final manuscript, and is the author responsible for archiving the study files.
Conflicts of Interest: Ken B. Johnson reported no conflicts of interest.
Name: Benjamin R. Randall, MD.
Contribution: This author helped conduct the study and analyze the data.
Attestation: Benjamin R. Randall has seen the original study data, reviewed the analysis of the data, and approved the final manuscript.
Conflicts of Interest: Benjamin R. Randall reported no conflicts of interest.
Name: Julia L. White, RN.
Contribution: This author helped design the study, conduct the study, and analyze the data.
Attestation: Julia L. White has seen the original study data, reviewed the analysis of the data, and approved the final manuscript.
Conflicts of Interest: Julia L. White reported no conflicts of interest.
Name: Talmage D. Egan, MD.
Contribution: This author helped design the study, conduct the study, analyze the data, and write the manuscript.
Attestation: Talmage D. Egan has seen the original study data, reviewed the analysis of the data, and approved the final manuscript.
Conflicts of Interest: Talmage D. Egan consulted for Scott Laboratories.